Abstract In this paper, we use self-determination theory and its related mini-theories to investigate the influence of sport data on sports experience and motivation in sports. First, we reflect on the use of technology in sports and show how sport data thwarts and promotes motivation in sports. Second, we argue that human–computer interaction (HCI) has been too narrowly focused on the ‘performance’ aspect of sport data. We argue for a more liberal take on sport data, showing that it also relates to motivation in sports through basic human needs. By bridging SportsHCI studies with the insights we gain from self-determination theory, we uncover the interwoven relations between the objective measures that sports technology provides and their motivational aspects for athletes. Our paper ends with five emerging points for attention for SportsHCI that we think can pave the way towards a more holistic approach to considering sport data for motivation in sports.

People's health goals change as their contexts, needs, and values evolve. Personal informatics (PI) literature recognizes the importance of supporting goal change; however, little is known about how these tools can best support the changes people go through with their goals. To understand how PI are currently involved in goal change, we conducted a survey (N=80) and interview (N=10) study with people who had recently changed their health goals. Overall, we found that PI gave limited support to people during goal changes. Changes were driven by four actors (i.e., who and what influences the goal change): internal motivations, contexts, PI, and social surroundings. We further highlight five factors related to goal change (i.e., the ways in which the actors affect goal change): challenge, self-efficacy, changing priorities, learning, and enjoyment. We discuss how PI could better support people in goal change by considering different implementations and interactions of actors and factors.

As artificial intelligence (AI) becomes more embedded in personal health technology, its potential to transform health decision-making through personalised recommendations is becoming significant. However, there is limited understanding of how individuals perceive AI-assisted decision-making in the context of personal health. This study investigates the impact of AI-assisted decision-making on trust in physical activity-related health decisions. By employing MoveAI, a GPT-4.0-based physical activity decision-making tool, we conducted a mixed-methods study and conducted an online survey (N=184) and semi-structured interviews (N=24) to explore this dynamic. Our findings emphasise the role of nuanced personal health recommendations and individual decision-making styles in shaping trust in AI-assisted personal health decision-making. This paper contributes to the HCI literature by elucidating the relationship between decision-making styles and trust in the AI-assisted personal health decision-making process and showing the challenges of aligning AI recommendations with individual decision-making preferences.

Research and technological advancements have driven the development of wearable technology for stress management. Previous reviews primarily focused on its performance and effectiveness in health contexts. In contrast, this review takes a human-centric approach and reviews studies on users’ attitudes and experiences. We conducted a narrative review to identify (1) the facilitators and barriers of wearable stress management technology (WSMT) and (2) design considerations for human-centered WSMT. We identified 28 articles reporting user perspectives on stress management technology, primarily based on evaluation studies in which user perspectives were gathered through qualitative methods. We found five facilitators and barriers of WSMT (i.e., usefulness, functionality/interactivity, seamlessness, user privacy, and technology's image). Additionally, we synthesized 18 design considerations, highlighted two main design challenges, and proposed a value-sensitive approach for future research. This review adds to the HCI literature by demonstrating the complexity of designing human-centered WSMT and the need for actionable recommendations.

Abstract Stress-tracking technology is becoming widely available and accessible, offering non-invasive ways to monitor and regulate stress. Yet, current stress-tracking technology presents stress scores that lack transparency, informativeness, and nuance. This provocation paper discusses five key issues that the current stress-tracking technology should overcome, involving conceptualization, measurements, transparency, interpretation, and responsibility. Next, we provide three directions to overcome these issues and inform better stress-tracking practices and future research. Future stress technology should improve stress response measurements, use better terminology and data visualizations, and increase user involvement and transparency. We conclude that there is a pressing need for designers and researchers to take greater responsibility in creating stress-tracking technologies that are useful, fair and just, and centered around individuals’ needs.

Abstract Improvements in self-tracking technology, particularly the integration of sports performance metrics with health data, have contributed to advancements in athletic performance. Meanwhile, there is a growing attention within HCI to menstrual health that emphasizes the role of technology within bodily experiences. Yet, despite the availability of self-tracking tools for both sports and menstrual health, there is still a gap in HCI which addresses the unique needs of menstruating athletes and the impacts of athletic performance on menstrual cycles and vice versa. To address this gap, we conducted a diary study and interviews with N = 11 runners to demonstrate how self-tracking technology supports menstruating athletes in recognising and navigating the interplay between athletic performance and menstrual cycles. Our results shed light on the challenges and coping strategies of menstruating athletes related to menstruation, and the way tracking tools address them. This paper suggests directions for interaction designers to tackle the challenges of bidirectional impacts of athletic performance and menstrual cycles.

The field of Sports Human-Computer Interaction (SportsHCI) investigates interaction design to support a physically active human being. Despite growing interest and dissemination of SportsHCI literature over the past years, many publications still focus on solving specific problems in a given sport. We believe in the benefit of generating fundamental knowledge for SportsHCI more broadly to advance the field as a whole. To achieve this, we aim to identify the grand challenges in SportsHCI, which can help researchers and practitioners in developing a future research agenda. Hence, this paper presents a set of grand challenges identified in a five-day workshop with 22 experts who have previously researched, designed, and deployed SportsHCI systems. Addressing these challenges will drive transformative advancements in SportsHCI, fostering better athlete performance, athlete-coach relationships, spectator engagement, but also immersive experiences for recreational sports or exercise motivation, and ultimately, improve human well-being.

Training Load Management (TLM) is crucial for achieving optimal athletic performance and preventing chronic sports injuries. Current sports trackers provide runners with data to manage their training load. However, little is known about the extent and the way sports trackers are used for TLM. We conducted a survey (N=249) and interviews (N=24) with runners to understand sports tracker use in TLM practices. We found that runners possess some understanding of training load and generally trust their trackers to provide accurate training load-related data. Still, they hesitate to strictly follow trackers’ suggestions in managing their training load, often relying on their intuitions and body signals to determine and adapt training plans. Our findings contribute to SportsHCI research by shedding light on how sports trackers are incorporated into TLM practices and providing implications for developing trackers that better support runners in managing their training load.

Research has extensively explored how personal informatics tools can support people's health goal setting practices. To understand the current state and reflect on the future of goal setting in personal informatics, we report the results of a scoping review of 51 papers that use and provide design implications for implementing goal setting. Our review highlights six implications for using goal setting in personal informatics tools (clarity, transparency, flexibility, framing and reframing, personalization, and reflection). We find that goal setting is becoming increasingly complex as the number of goals and their characteristics increase. We discuss these insights and point towards the importance of supporting self-efficacy during goal setting, showing adaptive goal evolution over time, reducing burden during goal setting, and framing goals to understand the complexity of health goals and support a holistic view on goal setting.

Hand rehabilitation aims to improve patients’ hand and arm skills, improve adherence to training and increase their participation in activities of daily living (ADLs). A novel way of achieving this is to employ ADL-based interactive rehabilitation tools and show patients how their improved skills can be transferable to daily tasks. Hence, in this paper, we report the results of a set of studies carried out with six healthy individuals and two physiotherapists to discover the potential of integrating ADLs into interactive hand rehabilitation tools. Consequently, we designed two interactive drinking-based concepts and tested those with three stroke patients. We found that ADL-based training couples particularly well with functional training. Still, selecting appropriate functional exercises that match the ADL is an essential task to transfer training outcomes to a functional setting. Based on our findings, this paper highlights that ADL-based interactive hand rehabilitation training must minimally deviate from the original ADLs.

Human-Computer Interaction (HCI) researchers have been increasingly interested in investigating self-trackers’ experience with self-tracking tools (STT) to get meaningful insights from their data. However, the literature lacks a coherent, integrated and dedicated source on designing tools that support self-trackers’ sensemaking practices. To address this, we carried out a systematic literature review by synthesizing the findings of 91 articles published before 2021 in HCI literature. We identified four data sensemaking modes that self-trackers go through (i.e., self-calibration, data augmentation, data handling, and realization). We also identified four design implications for designing self-tracking tools that support self-trackers’ data sensemaking practices (i.e., customized tracking experience, guided sensemaking, collaborative sensemaking, and learning sensemaking through self-experimentation). We provide a research agenda with nine directions for advancing HCI studies on data sensemaking practices. With these contributions, we created an analytical information source that could guide designers and researchers in understanding, studying, and designing for self-trackers’ data sensemaking practices.

Impaired hand function impacts many stroke patients’ daily lives, leading to a lack of independence and difficulty in performing activities of daily living (ADL). There are various assistive devices and interactive exercise monitoring systems that aim to help stroke patients perform unsupervised at-home hand rehabilitation exercises. However, for these efforts to work, the patients are required to self-supervise their rehabilitation process at home and allocate time in their daily schedule, which often is challenging. In this paper, we propose an alternative method. We hypothesize and test the idea of seamlessly integrating hand rehabilitation exercises with the products used for cooking. To this aim, we followed a research through design approach, developed Gr!pp and tested it with two stroke patients. Our results show that Gr!pp can facilitate intuitive use by its form. We also found other application areas of Gr!pp (e.g., eating) and improvement points (e.g., gamification) to promote motivation. We conclude our paper with further implications and our contribution to the tangible interaction design field.

User experience evolves in accordance with users’ attitudes, habits, and personality, as well as their prior experiences. Even though there are attempts to holistically frame the long-term experience of interactive products, there is still debate on how to guide designers in the design process of those products. To tackle this issue, this paper proposes the usage of Path of Long-Term User Experience (PLUX) model in design process. To interrogate the usefulness of the model, we conducted two studies. First, we adopted, adapted and tested the applicability of the backcasting approach, together with the visual materials that could be used in the design process. Following this, we tested the effectiveness of using the PLUX model as a guidance tool in designing interactive products. The PLUX model together with the backcasting approach helps designers to better ground their decisions in the design process and to find ways to enrich long-term user experience. The stages of user experience as well as the human and product-related qualities of the PLUX model facilitated in-depth reflection, and espoused creative interpretations of these qualities for ideation. However, the high level of detail is found limiting at times, depending on the ways the model is utilised.